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Prospect Theory Based Individual Irrationality Modelling and Behavior Inducement in Pandemic Control

Computer Modeling in Engineering & Sciences 2024年第7期140卷 139-170页

作者： Wenxiang Dong H.Vicky Zhao Department of Automation BNRistTsinghua UniversityBeijing100084China

Understanding and modeling individuals’behaviors during epidemics is crucial for effective epidemic control.However,existing research ignores the impact of users’irrationality on decision-making in the epidemic.Meanwhile,existing disease control methods often assume users’full compliance with measures like mandatory isolation,which does not align with the actual situation.To address these issues,this paper proposes a prospect theorybased framework to model users’decision-making process in epidemics and analyzes how irrationality affects individuals’behaviors and epidemic dynamics.According to the analysis results,irrationality tends to prompt conservative behaviors when the infection risk is low but encourages risk-seeking behaviors when the risk is high.Then,this paper proposes a behavior inducement algorithm to guide individuals’behaviors and control the spread of disease.Simulations and real user tests validate our analysis,and simulation results show that the proposed behavior inducement algorithm can effectively guide individuals’behavior.

关键词： disease spread behavior model irrationality prospect theory

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Quantifying the impacts of human mobility restriction on the spread of coronavirus disease 2019:an empirical analysis from 344 cities of China

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Chinese Medical Journal 2021年第20期134卷 2438-2446页

作者： Jing Tan Shao-Yang Zhao Yi-Quan Xiong Chun-Rong Liu Shi-Yao Huang Xin Lu Lehana Thabane Feng Xie Xin Sun Wei-Min Li Chinese Evidence-Based Medicine Center National Clinical Research Center for GeriatricsWest China HospitalSichuan UniversityChengduSichuan 610041China Department of Health Research Methods Evidenceand ImpactMcMaster UniversityHamiltonOntario L8S 4L8Canada Biostatistics Unit St Joseph’s Healthcare-HamiltonOntario L8S 4L8Canada School of Economics Sichuan UniversityChengduSichuan 610041China College of Systems Engineering National University of Defense TechnologyChangshaHunan 410073China Department of Global Public Health Karolinska InstituteStockholmSweden Center for Health Economics and Policy Analysis Department of Health Research MethodsEvidenceand ImpactMcMaster UniversityHamiltonOntario L8S 4L8Canada Department of Respiratory and Critical Care Medicine West China HospitalSichuan UniversityChengduSichuan 610041China

Background:Since the outbreak of coronavirus disease 2019(COVID-19),human mobility restriction measures have raised controversies,partly because of the inconsistent findings.An empirical study is promptly needed to reliably assess the causal effects of the mobility restriction.The purpose of this study was to quantify the causal effects of human mobility restriction on the spread of COVID-19.Methods:Our study applied the difference-in-difference(DID)model to assess the declines of population mobility at the city level,and used the log-log regression model to examine the effects of population mobility declines on the disease spread measured by cumulative or new cases of COVID-19 over time after adjusting for confounders.Results:The DID model showed that a continual expansion of the relative declines over time in 2020.After 4 weeks,population mobility declined by-54.81%(interquartile range,-65.50%to-43.56%).The accrued population mobility declines were associated with the significant reduction of cumulative COVID-19 cases throughout 6 weeks(ie,1%decline of population mobility was associated with 0.72%[95%CI:0.50%-0.93%]reduction of cumulative cases for 1 week,1.42%2 weeks,1.69%3 weeks,1.72%4 weeks,1.64%5 weeks,and 1.52%6 weeks).The impact on the weekly new cases seemed greater in the first 4 weeks but faded thereafter.The effects on cumulative cases differed by cities of different population sizes,with greater effects seen in larger cities.Conclusions:Persistent population mobility restrictions are well deserved.Implementation of mobility restrictions in major cities with large population sizes may be even more important.

关键词： Coronavirus disease 2019 Mobility restriction disease spread Causal effects

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Controlling disease spread on networks with feedback mechanism

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Chinese Physics B 2007年第9期16卷 2498-2502页

作者：王俐颜家壬张建国刘自然 Department of Physics Hunan Normal University Changsha 410081 China

Many real-world networks have the ability to adapt themselves in response to the state of their nodes. This paper studies controlling disease spread on network with feedback mechanism, where the susceptible nodes are able to avoid contact with the infected ones by cutting their connections with probability when the density of infected nodes reaches a certain value in the network. Such feedback mechanism considers the networks＇ own adaptivity and the cost of immunization. The dynamical equations about immunization with feedback mechanism ave solved and theoretical predictions are in agreement with the results of large scale simulations. It shows that when the lethality a increases, the prevalence decreases more greatly with the same immunization g. That is, with the same cost, a better controlling result can be obtained. This approach offers an effective and practical policy to control disease spread, and also may be relevant to other similar networks.

关键词： complex network systems disease spread feedback mechanism

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Interactive effects between travel behaviour and COVID-19:a questionnaire study

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Transportation Safety and Environment 2021年第2期3卷 166-177页

作者： Jinbao Zhang Jaeyoung Lee School of Traffic and Transportation Engineering Central South UniversityChangsha 410075China

This study has two main objectives:(i)to analyse the effect of travel characteristics on the spreading of disease,and(ii)to determine the effect of COVID-19 on travel behaviour at the individual level.First,the study analyses the effect of passenger volume and the proportions of different modes of travel on the spread of COVID-19 in the early stage.The developed spatial autoregressive model shows that total passenger volume and proportions of air and railway passenger volumes are positively associated with the cumulative confirmed cases.Second,a questionnaire is analysed to determine changes in travel behaviour after COVID-19.The results indicate that the number of total trips considerably decreased.Public transport usage decreased by 20.5%,while private car usage increased by 6.4%.Then the factors affecting the changes in travel behaviour are analysed by logit models.The findings reveal significant factors,including gender,occupation and travel restriction.It is expected that the findings from this study would be helpful for management and control of traffic during a pandemic.

关键词： COVID-19 transportation system questionnaire survey disease spread pandemic

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